In signal processing associated with wireless devices, the singular value decomposition is frequently used to process signals. The singular value decomposition is a factorization of a rectangular real or a complex matrix. For example, the singular value decomposition is a decomposition that may include determining a pseudoinverse, a least squares fitting of data, a matrix approximation, and determining the rank, the range and/or the null space of a matrix. As such, the singular value decomposition is a computationally intensive operation, which in the case of a wireless device, may be problematic. Moreover, in many implementations, the singular value decomposition is an iterative solution, not of a closed form.
Multiple-input and multiple-output (MIMO) is typically used in wireless communications to enhance performance, when compared to non-MIMO approaches. For example, multiple antennas may be implemented at the transmitter and/or the receiver to improve performance by providing, in some implementations, enhanced throughput and range. Often, these performance enhancements may be obtained without substantial increases in transmitted power and/or bandwidth, hence the appeal of MIMO. However, MIMO typically comes at the cost of complex processing, including complex singular value decomposition processing, at the transmitter and at the receiver